Shikha Nayar

1.4k total citations
10 papers, 305 citations indexed

About

Shikha Nayar is a scholar working on Genetics, Immunology and Surgery. According to data from OpenAlex, Shikha Nayar has authored 10 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Genetics, 4 papers in Immunology and 3 papers in Surgery. Recurrent topics in Shikha Nayar's work include Inflammatory Bowel Disease (4 papers), Immune cells in cancer (3 papers) and Microscopic Colitis (2 papers). Shikha Nayar is often cited by papers focused on Inflammatory Bowel Disease (4 papers), Immune cells in cancer (3 papers) and Microscopic Colitis (2 papers). Shikha Nayar collaborates with scholars based in United States, Canada and India. Shikha Nayar's co-authors include Judy H. Cho, Jaime Chu, Mamta Giri, Ling-Shiang Chuang, Subra Kugathasan, Huaibin M. Ko, Kyle Gettler, Charles DeRossi, Ephraim Kenigsberg and Laura Walker and has published in prestigious journals such as Nature, Gut and Molecular Biology of the Cell.

In The Last Decade

Shikha Nayar

10 papers receiving 304 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Shikha Nayar United States	8	128	105	88	56	42	10	305
Mamta Giri United States	10	127 1.0×	95 0.9×	80 0.9×	49 0.9×	31 0.7×	12	268
Weigang Shu China	8	147 1.1×	142 1.4×	103 1.2×	54 1.0×	63 1.5×	10	366
Irmgard Neumaier Germany	7	176 1.4×	141 1.3×	82 0.9×	66 1.2×	69 1.6×	10	410
Ritian Lin China	12	164 1.3×	133 1.3×	81 0.9×	55 1.0×	43 1.0×	17	341
Cheng-Rui Li United States	7	72 0.6×	214 2.0×	55 0.6×	35 0.6×	37 0.9×	8	345
Chengxiang Wu United States	11	159 1.2×	74 0.7×	57 0.6×	20 0.4×	66 1.6×	25	391
Inne Crèvecoeur Belgium	8	108 0.8×	90 0.9×	147 1.7×	118 2.1×	26 0.6×	9	355
Martina Rocchi Italy	7	167 1.3×	169 1.6×	67 0.8×	37 0.7×	60 1.4×	11	398
Markus Tschurtschenthaler Germany	10	179 1.4×	127 1.2×	51 0.6×	56 1.0×	106 2.5×	23	419
Wen Shi China	13	95 0.7×	189 1.8×	43 0.5×	42 0.8×	52 1.2×	21	387

Countries citing papers authored by Shikha Nayar

Since Specialization

Citations

This map shows the geographic impact of Shikha Nayar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shikha Nayar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shikha Nayar more than expected).

Fields of papers citing papers by Shikha Nayar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shikha Nayar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shikha Nayar. The network helps show where Shikha Nayar may publish in the future.

Co-authorship network of co-authors of Shikha Nayar

This figure shows the co-authorship network connecting the top 25 collaborators of Shikha Nayar. A scholar is included among the top collaborators of Shikha Nayar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shikha Nayar. Shikha Nayar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

DeRossi, Charles, Shikha Nayar, Mamta Giri, et al.. (2022). Single‐cell transcriptomics reveals conserved cell identities and fibrogenic phenotypes in zebrafish and human liver. Hepatology Communications. 6(7). 1711–1724. 32 indexed citations

2.

Hsu, Nai-Yun, Shikha Nayar, Kyle Gettler, et al.. (2022). NOX1 is essential for TNFα-induced intestinal epithelial ROS secretion and inhibits M cell signatures. Gut. 72(4). 654–662. 43 indexed citations

3.

Nayeri, Shadi, Jiayi Ji, Cristian Hernández-Rocha, et al.. (2021). A Role for CXCR3 Ligands as Biomarkers of Post-Operative Crohn’s Disease Recurrence. Journal of Crohn s and Colitis. 16(6). 900–910. 15 indexed citations

4.

Nayar, Shikha & Judy H. Cho. (2021). From single-target to cellular niche targeting in Crohn's disease: intercepting bad communications. EBioMedicine. 74. 103690–103690. 3 indexed citations

5.

Nayar, Shikha, Mamta Giri, Kyle Gettler, et al.. (2021). A myeloid–stromal niche and gp130 rescue in NOD2-driven Crohn’s disease. Nature. 593(7858). 275–281. 82 indexed citations

6.

Ungaro, Ryan C., Liangyuan Hu, Jiayi Ji, et al.. (2020). Machine learning identifies novel blood protein predictors of penetrating and stricturing complications in newly diagnosed paediatric Crohn's disease. Alimentary Pharmacology & Therapeutics. 53(2). 281–290. 32 indexed citations

7.

Madhu, S. V. & Shikha Nayar. (2020). Glycemic index of wheat and rice are similar when consumed as part of a North Indian mixed meal. Indian Journal of Endocrinology and Metabolism. 24(3). 251–251. 7 indexed citations

8.

Chuang, Ling-Shiang, Nai‐Yun Hsu, Philippe Ronel Labrias, et al.. (2019). Zebrafish modeling of intestinal injury, bacterial exposures and medications defines epithelial in vivo responses relevant to human inflammatory bowel disease. Disease Models & Mechanisms. 12(8). 32 indexed citations

9.

Shtraizent, Nataly, Charles DeRossi, Shikha Nayar, et al.. (2017). MPI depletion enhances O-GlcNAcylation of p53 and suppresses the Warburg effect. eLife. 6. 29 indexed citations

10.

DeRossi, Charles, Ana M. Vacaru, Ayca Cinaroglu, et al.. (2016). trappc11is required for protein glycosylation in zebrafish and humans. Molecular Biology of the Cell. 27(8). 1220–1234. 30 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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